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  1. With an increase in the need for energy efficient data centers, a lot of research is being done to maximize the use of Air Side Economizers (ASEs), Direct Evaporative Cooling (DEC), Indirect Evaporative Cooling (IEC) and multistage Indirect/Direct Evaporative Cooling (I/DEC). The selection of cooling configurations installed in modular cooling units is based on empirical/analytical studies and domain knowledge that fail to account for the nonlinearities present in an operational data center. In addition to the ambient conditions, the attainable cold aisle temperature and humidity is also a function of the control strategy and the cooling setpoints in the data center.The primary objective of this study is to use Artificial Neural Network (ANN) modelling and Psychrometric bin analysis to assess the applicability of various cooling modes to a climatic condition. Training dataset for the ANN model is logged from the monitoring sensor array of a modular data center laboratory with an I/DEC module. The data-driven ANN model is utilized for predicting the cold aisle humidity and temperatures for different modes of cooling. Based on the predicted cold aisle temperature and humidity, cold aisle envelopes are represented on a psychrometric chart to evaluate the applicability of each cooling mode to the territorial climatic condition. Subsequently, outside air conditions favorable to each cooling mode in achieving cold aisle conditions, within the ASHRAE recommended environmental envelope, is also visualized on a psychrometric chart. Control strategies and opportunities to optimize the cooling system are discussed. 
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  2. The objective of this work is to introduce the application of an artificial neural network (ANN) to assist in the evaporative cooling in data centers. To achieve this task, we employ the neural network algorithms to predict weather conditions outside the data center for direct evaporative cooling (DEC) operations. The predictive analysis helps optimize the cooling control strategy for maximizing the usage of evaporative cooling thereby improving the efficiency of the overall data center cooling system. A typical artificial neural network architecture is dynamic in nature and can perform adaptive learning in minimal computation time. A neural network model of a data center was created using operational historical data collected from a data center cooling control system. The neural network model allows the control of the modular data center (MDC) cooling at optimum configuration in two ways. First way is that the network model minimizes time delay for switching the cooling from one mode to the other. Second way, it improves the reaction behavior of the cooling equipment if an unexpected ambient condition change should come. The data center in consideration is a test bed modular data center that comprises of information Technology (IT) racks, Direct Evaporative cooling (DEC) and Indirect Evaporative Cooling (IEC) modules; the DEC/IEC are used together or in alternative mode to cool the data center room. The facility essentially utilizes outside ambient temperature and humidity conditions that are further conditioned by the DEC and IEC to cool the electronics, a concept know as air-side economization. Various parameters are related to the cooling system operation such as outside air temperature, IT heat load, cold aisle temperature, cold aisle humidity etc. are considered. Some of these parameters are fed into the artificial neural network as inputs and some are set as targets to train the neural network system. After the training the process is completed, certain bucket of data is tested and further used to validate the outputs for various other weather conditions. To make sure the analysis represents real world scenario, the operational data used are from real time data logged on the MDC cooling control unit. Overall, the neural network model is trained and is used to successfully predict the weather conditions and cooling control parameters. The prediction models have been demonstrated for the outputs that are static in nature (Levenberg Marquardt method) as well as the outputs that are dynamic in nature i.e., step-ahead & multistep ahead techniques. 
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  3. Rigid wet cooling media is a key component of direct and indirect evaporative cooling systems. Evaporation is the process of a substance in a liquid state changing to a gaseous state. When water evaporates only water molecules get evaporated and the other chemicals in the water are left behind on the surface as residue. Many studies have been conducted on how the change in air flow velocity, media depth, porosity and water distribution affect performance of the cooling system. The operational efficiency of the cooling media varies over its life cycle and depends primarily on temperature and speed of inlet air, water distribution system, type of pad and dimension of the pad.Although evaporative cooling when implemented with air-side economization enables efficiency gains, a trade-off between the system maintenance and its operational efficiency exists. In this study, the primary objective is to determine how calcium scale affects the overall performance of the cooling pad and the water system. Areas of the pad that are not wetted effectively allow air to pass through without being cooled and the edges between wetted and dry surface establish sites for scale formation. An Accelerated Degradation Testing (ADT) by rapid wetting and drying on the media pads at elevated levels of calcium is designed and conducted on the cellulose wet cooling media pad. This research focuses on monitoring the degradation that occurs over its usage and establish a key maintenance parameter for water used in media pad.As a novel study, preliminary tests were mandatory because there were no established standards for media pad degradation testing. Sump water conductivity is identified as the key maintenance parameter for monitoring sump replenishing and draining cycles which will result in reduced water usage. The average water conductivity in the sump during wetting cycles increases monotonically when ADT was performed on a new media pad. An empirical relationship between sump water conductivity and number of wetting cycles is proposed. This information will be very helpful for the manufacturers to guide their customers for maintenance of the media pad and sump water drain cycles. 
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  4. When operating in direct evaporative cooling (DEC) mode, the amount of moisture added to a system can be controlled by frequently modulating water supply to the wet cooling media. Though many challenges arise due to geographical and site conditions, this concept can be applied to data centers to serve as a cost-effective alternative for maintaining the operating temperature of the facility at any weather condition. However, this method results in scale and mineral build up on the media because of an irregular water distribution. To prevent the scale formation, the operators allow the water supply continuously on the cooling media ultimately leading towards the high consumption of facility water and significantly deteriorating the Wet cooling media life. This challenge has been addressed for the first time by experimentally characterizing the vertically split distribution wet cooling media. These systems allow some section of the media to be wetted while other sections remain dry. Various configuration of vertically staged media may be achieved by dividing the full width of the media into two, three, four or more number of equal and unequal sections and providing individually controlled water distribution headers. To increase the number of stages and provide smooth transition from one stage to the other, a MATLAB code is written to find width of DEC media sections for known total width of the media and number of sections. Here, an experimental design to characterize the performance characteristics of a vertically split wet cooling media which has separate water distribution setup has been presented. Apart from relative humidity and temperature, other parameters of interests like pressure drop across the media and saturation efficiency of the rigid media are presented. In the unequal configuration, the media was tested for 0%, 33%, 66%, and 100%. This research provides a potential solution towards the limitation of direct evaporative cooling in terms of energy savings, facility water, reliability and contaminants. 
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